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5 Trends Highlight Mainframe's Continued Value to Business

The State of the Mainframe report from Syncsort revealed an increased focus on traditional data infrastructure optimization to control costs and help fund strategic organizational projects like AI, machine learning and predictive analytics in addition to widespread concern about meeting security and compliance requirements.

The study, which polled over 220 respondents from a wide range of IT disciplines including executives, architects, system programmers, application analysts, database administrators, operations managers and security professionals, identified five trends that reflect the vital role mainframe data plays in supporting business and operational intelligence initiatives:

1. Mainframe infrastructure optimization enables new strategic projects

The mainframe remains strategic to businesses, with 57% of respondents stating it will continue to be the main hub for business-critical applications this year, and where 43% will run revenue-generating services. Given the mainframe’s key role in so many organizations, cost control is a priority: 51% said they planned to cut IT costs by optimizing mainframe resources.

2. Cost reduction, security and compliance continue to be top challenges

Reducing general processor CPU usage and related costs (70%), meeting security and compliance requirements (63%) and meeting SLAs (55%) again ranked as the top three challenges organizations face in 2018. To improve performance and save money, 56% of respondents are leveraging their investment in zIIP engines while 44% are increasing their DB2 performance.

3. Integrating mainframe data with modern analytics tools enables enterprise-wide data views

44% of respondents chose integrating mainframe data with modern analytics tools as a top organizational priority, and 23% said they already use Big Data tools (like Splunk and Hadoop) to monitor mainframe and other enterprise data together in a single dashboard.

4. System Management Facilities (SMF) and z/OS log data will play an increased role in addressing security and compliance mandates

54% of respondents ranked monitoring SMF and log file data as most important for security on the mainframe, followed closely by having an audit trail of SMF data (53%) and regularly auditing and reviewing incident response (52%).

5. Mainframe data analysis and movement across platforms is a priority

Mainframe organizations continue to find tracking their data a challenge: 53% of organizations say they lack full visibility into their data movement, compared with 61% last year. While the downward trend is encouraging, this remains an area of risk that must be addressed to ensure security and compliance initiatives are met.

The study also showed that mainframe environments remain a place of robust investment. In fact, 32% of respondents report increased spending for developing new mainframe applications compared with just 24% last year, and another 32% reported increased investment in mainframe data analytics.

“It’s clear that traditional data environments, including mainframe and IBM i, remain central to large enterprises’ business,” said David Hodgson, Chief Product Officer, Syncsort. “Our annual State of the Mainframe research confirms what we are seeing across our more than 7,000 customers worldwide: while many are turning to Big Data analytics platforms to meet compliance and security requirements, they continue to successfully use the mainframe and IBM i to run revenue-generating services, requiring them to optimize their data infrastructure to improve performance and control costs.”

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5 Trends Highlight Mainframe's Continued Value to Business

The State of the Mainframe report from Syncsort revealed an increased focus on traditional data infrastructure optimization to control costs and help fund strategic organizational projects like AI, machine learning and predictive analytics in addition to widespread concern about meeting security and compliance requirements.

The study, which polled over 220 respondents from a wide range of IT disciplines including executives, architects, system programmers, application analysts, database administrators, operations managers and security professionals, identified five trends that reflect the vital role mainframe data plays in supporting business and operational intelligence initiatives:

1. Mainframe infrastructure optimization enables new strategic projects

The mainframe remains strategic to businesses, with 57% of respondents stating it will continue to be the main hub for business-critical applications this year, and where 43% will run revenue-generating services. Given the mainframe’s key role in so many organizations, cost control is a priority: 51% said they planned to cut IT costs by optimizing mainframe resources.

2. Cost reduction, security and compliance continue to be top challenges

Reducing general processor CPU usage and related costs (70%), meeting security and compliance requirements (63%) and meeting SLAs (55%) again ranked as the top three challenges organizations face in 2018. To improve performance and save money, 56% of respondents are leveraging their investment in zIIP engines while 44% are increasing their DB2 performance.

3. Integrating mainframe data with modern analytics tools enables enterprise-wide data views

44% of respondents chose integrating mainframe data with modern analytics tools as a top organizational priority, and 23% said they already use Big Data tools (like Splunk and Hadoop) to monitor mainframe and other enterprise data together in a single dashboard.

4. System Management Facilities (SMF) and z/OS log data will play an increased role in addressing security and compliance mandates

54% of respondents ranked monitoring SMF and log file data as most important for security on the mainframe, followed closely by having an audit trail of SMF data (53%) and regularly auditing and reviewing incident response (52%).

5. Mainframe data analysis and movement across platforms is a priority

Mainframe organizations continue to find tracking their data a challenge: 53% of organizations say they lack full visibility into their data movement, compared with 61% last year. While the downward trend is encouraging, this remains an area of risk that must be addressed to ensure security and compliance initiatives are met.

The study also showed that mainframe environments remain a place of robust investment. In fact, 32% of respondents report increased spending for developing new mainframe applications compared with just 24% last year, and another 32% reported increased investment in mainframe data analytics.

“It’s clear that traditional data environments, including mainframe and IBM i, remain central to large enterprises’ business,” said David Hodgson, Chief Product Officer, Syncsort. “Our annual State of the Mainframe research confirms what we are seeing across our more than 7,000 customers worldwide: while many are turning to Big Data analytics platforms to meet compliance and security requirements, they continue to successfully use the mainframe and IBM i to run revenue-generating services, requiring them to optimize their data infrastructure to improve performance and control costs.”

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If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

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